On‐site forensic analysis of colored seized materials: Detection of brown heroin and MDMA‐tablets by a portable NIR spectrometer

Abstract The increasing workload for forensic laboratories and the expanding complexity of the drug market necessitates efficient approaches to detect drugs of abuse. Identification directly at the scene of crime enables investigative forces to make rapid decisions. Additionally, on‐site identification of the material also leads to considerable efficiency and cost benefits. As such, paperwork, transportation, and time‐consuming analysis in a laboratory may be avoided. Near‐infrared (NIR) spectroscopy is an analysis technique suitable for rapid drug testing using portable equipment. A possible limitation of spectroscopic analysis concerns the complexity of seized materials. NIR measurements represent composite spectra for mixtures and diagnostic spectral features can be obscured by excipients such as colorants. Herein, a NIR‐based (1300–2600 nm) detection of heroin and MDMA in colored casework (i.e., brown powders and ecstasy tablets) using a portable analyzer is presented. The application includes a multistage data analysis model based on the net analyte signal (NAS) approach. This identification model was specifically designed for mixture analysis and requires a limited set of pure reference spectra only. Consequently, model calibration efforts are reduced to a minimum. A total of 549 forensic samples was tested comprising brown heroine samples and a variety of colored tablets with different active ingredients. This investigation led to a >99% true negative and >93% true positive rate for heroin and MDMA. These results show that accurate on‐site detection in colored casework is possible using NIR spectroscopy combined with an efficient data analysis model. These findings may eventually help in the transition of routine forensic laboratories from laboratory‐based techniques to portable equipment operated on scene.

analysis in a laboratory may be avoided. Near-infrared (NIR) spectroscopy is an analysis technique suitable for rapid drug testing using portable equipment. A possible limitation of spectroscopic analysis concerns the complexity of seized materials. NIR measurements represent composite spectra for mixtures and diagnostic spectral features can be obscured by excipients such as colorants. Herein, a NIR-based (1300-2600 nm) detection of heroin and MDMA in colored casework (i.e., brown powders and ecstasy tablets) using a portable analyzer is presented. The application includes a multistage data analysis model based on the net analyte signal (NAS) approach. This identification model was specifically designed for mixture analysis and requires a limited set of pure reference spectra only. Consequently, model calibration efforts are reduced to a minimum. A total of 549 forensic samples was tested comprising brown heroine samples and a variety of colored tablets with different active ingredients. This investigation led to a >99% true negative and >93% true positive rate for heroin and MDMA. These results show that accurate on-site detection in colored casework is possible using NIR spectroscopy combined with an efficient data analysis model. These findings may eventually help in the transition of routine forensic laboratories from laboratory-based techniques to portable equipment operated on scene.
K E Y W O R D S colored samples, forensic casework analysis, illicit drug analysis, near-infrared spectroscopy, portable devices

| INTRODUCTION
Opioid drugs (such as heroin) and amphetamine-type stimulants (such as MDMA) are among the most produced, traded, and consumed drug categories worldwide. 1 Unlike cocaine that typically has an appearance as a white or lightly colored powder, heroin street samples are generally of a beige, brown, or dark brown complexion. Ecstasy, a regular formulation of MDMA, appears as tablets in a wide range of different and often exuberant colors.
Although both crude heroin and MDMA may have a brown color due to impurities originating from the manufacturing process, the color of street samples in most cases originates from deliberately added colorants. Paracetamol and caffeine are the most commonly used adulterants in heroin. These adulterants are white powders in their pure form. To mask dilution, paracetamol-caffeine mixtures itself are often given a brown color by the use of dyes. 2 Synthetic colorants brilliant black (E151), sunset yellow (E110), and tartrazine (E102) have been identified in brown heroin casework samples. 3 Ecstasy tablets have a large variety of shapes, imprints, and colors to make them aesthetically appealing. Common commercially available food colorants such as azo dyes are regularly used for this purpose. 4,5 Forensic drug testing laboratories are demanding reliable methods for rapid on-scene detection of these illicit substances in suspected casework materials. Traditionally, colorimetric spot tests are used for this purpose although their applicability is only limited to substances for which such a test is available. Additionally, these tests require a chemical reaction with the suspected material that often involves strong acids and thus may pose a safety risk when performed on-site. 6 In recent years, on-site drug detection by portable spectroscopic techniques such as Raman, 7,8 Fourier transform infrared (FTIR), 9 and near-infrared (NIR) became readily accessible and were also used for casework analysis in the forensic field. 10,11 NIR is a powerful noninvasive technique for fast and efficient substance detection due to the availability of small size instrumentation (handheld, pocket size, smartphone sensor 12 ) at relatively low cost. 13,14 Recent applications of NIR detection in the forensic drug testing field include the detection of cocaine, [15][16][17][18][19] "legal high" designer drugs, 20 ketamine, heroin, and methamphetamine. 15 All these implementations mainly focus on lightly colored (i.e., white) powdered samples.
Eliaerts et al in 2021 reported on the challenges that colored samples may pose in forensic drug detection by dyes or pigments obscuring diagnostic spectroscopic signals. 21 31 In a follow-up study, they improved the performance by implementing an uninformative variable elimination approach as preselection for PLS. 32 Additionally, they provided insight in the origin of diagnostic spectral peaks for heroin (in its base form).
In earlier work, our group reported the NIR spectrum of MDMA HCl in the implementation of a calibration-friendly approach for mixture analysis in forensic samples that were predominantly white powders. 17 Only a very limited number of studies reported on NIR-based MDMA detection. In 1999, Sondermann and Kovar performed NIR analyses on both intact and pulverized tablets using a benchtop instrument operating in the 1100-2500 nm range. They showed that MDMA detection is possible using PLS modeling. [33][34][35] It is noteworthy that the reported MDMA HCl spectrum in these studies was different from the spectra recorded by our group. 17,36 These differences were attributed to different hydrated and anhydrous polymorphous forms of MDMA HCl. 35,37 This indicates that the MDMA used in these studies was either dried to convert the hydrates into anhydrates or was synthesized in the clandestine laboratory in an anhydrous way.
To our knowledge, only one earlier study has reported on MDMA detection in colored casework materials (i.e., ecstasy tablets) using portable NIR instruments. Tsujikawa et al 37 developed a library search-based screening for MDMA using a portable 1400-2400 nm NIR spectrometer.
A plausible explanation for the lack of NIR-based studies for MDMA or heroin detection is the perceived detrimental influence of the complex mixture matrix and appearance as, for example, tablets or chunks. Portable NIR spectrometers operating below $1000 nm were generally found unsuitable for illicit drug detection in colored samples due to the major influence of colorants in this wavelength range 16,36 combined with a limited number of spectral features of MDMA. 36 Both a wider and higher wavelength range of the NIR spectrum (above 1000 and up to 2600 nm) is suggested for MDMA detection due to specific spectral features in this range. 17 Additionally, the spectral fingerprint obtained from forensic casework is a combination of signals from all constituents in the sample material. As adulterants (e.g., caffeine and paracetamol), impurities (e.g., papaverine and noscapine), and excipients (e.g., tablet fillers microcrystalline cellulose and lactose) are commonly present in casework and contribute to the spectral signal, advanced data processing tools and models are required for successful identification.
In this study, we present a novel application to detect common drugs of abuse in colored forensic samples using portable NIR technology, with a focus on heroin and MDMA. Based on the calibration-free approach for mixture analysis introduced before and demonstrated for cocaine, 17

| Instrumentation and software
All NIR measurements were carried out on the Powder Puck. The hardware and data analysis software for forensic casework were developed for a previous study on cocaine samples and are described in more detail in an earlier report. 17 In short, the Powder Puck is a USB-controlled portable spectrometer that consists of a NeoSpectra sensor (Si-WARE, Cairo, Egypt). This sensor operates in the 1300-2600 nm range with a spectral resolution of 16 nm at 1550 nm. The raw spectral data (160 datapoints) were processed by an in-house developed MATLAB (Version 2020b Update 5) application: Second derivative spectra were projected onto a linear discriminant analysis (LDA) model based on a specifically selected matrix. The outcome of the LDA model serves as input to an optional subsequent mixture detection analysis using a NAS approach. The NAS model determines the optimal combination of library components that describes the unknown sample spectra best. The outcome of the software presents the user with a possible composition of the samples (either as a pure component or a mixture of components). Each identity result is accompanied with a similarity score that ranges between 0.00 and 1.00. A score of 1.00 indicates a match with a pure reference substance in the LDA model. A score between 0.00 and 0.99 originates from the subsequent NAS model and is a measure of the similarity between the recorded spectrum and the model result (calculated optimal fit with a substance or mixture at a given concentration). Herein, a higher score indicates a better similarity. For this study, a score above 0.80 is considered a confident identification by the software. A similarity score above 0.70 and ≤0.80 serves merely as an indication of the potential presence of a drug of abuse. Consequently, the corresponding sample could be sent to the laboratory for confirmatory analysis. Similarity scores ≤0.70 imply that no substance(s) from the given matrix was selected for identification purposes. This, therefore, is considered to be a negative result (no substance detected). For the purpose of this study, identifications with similarity scores >0.70 and ≤0.80 are also treated as negatives. Consequently, these outcomes are rated either as false or true negatives. It must be noted that these threshold levels were set by practical experience and may be further optimized for specific applications. A higher threshold will, for example, lead to less false positive results but may come with an increase of false negative results.

| NIR spectral selectivity of heroin and MDMA
The possibilities for heroin and MDMA detection in (colored) forensic casework by NIR spectroscopy were examined. As a first step, the associated NIR spectra and unique spectral features were visually inspected and compared with other relevant substances. Earlier studies already showed NIR spectra of MDMA and heroin, both yielding sufficient differences from other common drugs of abuse (e.g., cocaine, ketamine, and methamphetamine) to allow for their differentiation. 17,36 Similarly to cocaine, heroin may also occur in both its HCl salt or free base form in casework samples; typical brown heroin samples are reported to predominantly contain heroin base, whereas the more pure "white" heroin typically contains heroine HCl. 38 Unlike chromatographic methods (e.g., GC-MS) where samples are dissolved and converted into their native forms, direct spectroscopic analyses produce different spectra for different salt forms. 7,39 It is therefore important to include both heroin HCl and heroin base in the spectral library. Figure 1a shows the second derivative spectrum of heroin base compared with its two main cutting agents paracetamol (red trace) and caffeine (green trace) clearly showing differences (e.g., at $1800 and $2150 nm). Figure 1b shows the heroin base (black) reference spectrum in overlay with four brown heroin casework samples.
In three of these samples (brown to orange shades), the spectral features diagnostic for heroin can clearly be observed. The spectrum of the forth sample (red plot)-brown heroin sample H19 that is highly adulterated with paracetamol and caffein-clearly shows spectral features of the two adulterants (e.g., valley $2450 nm for paracetamol and peak $2300 nm for both paracetamol and caffeine) in combination with partly obscured signals for heroin. Figure 1c  shows that a data analysis approach focusing on mixture detection and spectral deconvolution may also be suitable for MDMA detection in forensic casework. Again, the raw spectra of all plots in Figure 2 can be found in Figure S2.

| Data analysis by the Powder Puck chemometric model
All 1516 spectra obtained from the 549 different forensic casework samples of the sample sets described in Section 2.1 were processed by the multistage chemometric model incorporated in the Powder Puck software. 17 One of the features of this software is the availability of user-selectable matrices for efficient analysis. This way, the user can select the most appropriate matrix based on their forensic expertise for a first analysis. For example, for white powdered samples, the cocaine matrix may be a first start, whereas for seized ecstasy tablets, an MDMA matrix may be profitable. In this study, two new matrices were developed, namely, the heroin matrix and the MDMA matrix. The results of this analysis are found in Data S1-S3. An overview of the results per sample set is shown in Table 1. Herein, a true positive is considered a result with a similarity score >0.80 that includes (optionally among others) the drug-of-abuse component present in the sample. All samples were analyzed in triplicate, except for the tablets in set T2 that were only scanned once. The results of Table 1 can thus also be presented on the sample level; these figures can be found in Table S1.
It must be noted all samples included in sets H, P, T, and T2 were diversely colored (including all regular hues) and that the samples in set M (MDMA crystals) ranged in color from cream to dark brown.
The purpose of sets C,D,N and PAM (predominantly white and offwhite powders) was to assess the selectivity of the model against a

| Heroin matrix library results
When looking at the heroin results, the most notable result is the total absence of false positives. Especially in forensic settings, a low false positive rate is important as this can have major adverse effects such as unjustified custody. Additionally, for a total of 10 scans, the presence of heroin was missed in a sample, thus resulting in a false negative. For seven out of these 10 scans, an indication for the presence of heroin was still given due to a heroin match with a similarity score between 0.70 and 0.80. The remaining three false negatives were the three replicates of sample H17, and for each scan, the sample was identified as a mixture of (only) paracetamol and caffeine. The GC-MS analysis revealed that this particular sample had a low heroin content in addition to larger quantities of paracetamol and caffein. Additionally, this sample contained small quantities of 6-monoacetylmorphine (6-MAM), a substance that was lacking in the matrix library due to the unavailability of a reference standard. All other 43 brown-colored powders were correctly identified as heroin-containing. It is noteworthy that in all these cases, heroin base was detected. The only instances in which heroin HCl was detected were "white heroin" samples with a pale (cream, off-white) color, namely, samples H8 and N23. The overall performance of the heroin matrix library is shown in Table 2, both in results per scan and results per sample. Individual sample results were determined by majority voting of the replicate scans. Generally, the performance of the heroin matrix library was more than satisfactory with a 93.2% true positive rate (6.8% false negative rate) and a 100% true negative rate (0% false positive rate). These spectra are overlaid with the spectra of the two false negatives:   Combined with the conclusions from earlier work on cocaine, 17 the results in this study show that the calibration friendly data analysis approach based on dedicated matrix libraries and mixture detection works sufficiently for various types of drugs-of-abuse casework.

| MDMA matrix libraries results
However, user knowledge is required to select the optimal matrix library based on the physical properties and expert recognition of the material (in analogy with colorimetric spot tests). Although multiple consecutive matrix libraries can be used to characterize the sample, this holds a risk of erroneous results due to the selection of the wrong library. An interesting future development may be to automatically process multiple libraries and report the result from the matrix library hit with the highest similarity score. Another option may be to expand the matrix library to include all frequently occurring drugs of abuse.
However, this requires additional validation on model performance.
The risk of erroneous results due to incompleteness of the matrix libraries could also be reduced by automatic monitoring of drug market developments to include NIR spectra of novel excipients in the library. A possible scenario is that samples with an inconclusive result or an unusually low match score are sent to the laboratory for detailed GC-MS analysis. If a new adulterant or excipient is detected this way, their reference NIR spectra can be added to the library to improve model performance in future samples.